SPECTRAL ANALYSIS OF HEART RATE VARIABILITY IN PATIENTS WITH CORONARY ARTERY DISEASE

Objective: To carryout frequency domain analysis ofheart rate variability in patients with coronary artery disease. Methods: Forty coronary artery disease patients with coronary artery stenosis greater than 70% of at least one vessel lumen were included. Patients with diabetes mellitus, atrial fibrillation, structural heart diseases and bundle branch block were excluded. DMS 300 4A Holter monitors were used to obtain long-term 12 lead digital ECG recordings. Cardio Scan premium luxury software was used for analysis of heart rate variability. Results: The mean values of heart rate variability in patients were TP (2171.70 ± 1028.7), VLF (1661.41 ± 807.88), LF (392.71 ± 227.92), HF (112.03 ± 77.90) and LF/HF ratio (4.03 ± 1.75). On comparison with normal reference values there was a significant decrease (p-value < 0.05) in all parameters except VLF (p-value = 0.351). TP was reduced in all the patients (100%), VLF in 26 (65%), LF in 36 (90%), HF in 36 (90%) and LF/HF ratio in 29 (72.5%) patients. The difference between the frequency of patients with decreased heart rate variability was statistically significant (p-value < 0.05) except VLF (p-value = 0.082). Conclusion: Heart rate variability decreases significantly in patients with coronary artery disease

Noncontact Measurement of Autonomic Nervous System Activities Based on Heart Rate Variability Using Ultra-Wideband Array Radar

The noncontact measurement of vital signs using ultra-wideband radar has been attracting increasing attention because it can unobtrusively provide information about the physical and mental condition of people. In particular, the continuous measurement of a person's time-varying instantaneous heart rate can estimate the activity level of the autonomic nervous system without the person wearing any sensors. Continuous heart rate measurement using radar is, however, a difficult task because accuracy is compromised by numerous factors, such as the posture and motion of the target person. In this study, we introduce techniques for increasing the accuracy and reliability of the noncontact measurement of heart rate variability. We demonstrate the performance of the proposed techniques by applying them to radar measurement data from a sleeping person, and we also compare its accuracy with electrocardiogram data